Shannon Millar
I'm a software engineer who is energized by
complex systems and building people-centric solutions.
![](https://portfolio-shannon-millar.s3.us-west-1.amazonaws.com/headshot-brick.jpeg)
My passion for people has always been embedded in my work as a consultant, data analyst, and now, as a software engineer, I remain eager to build data-driven websites that increase efficiency and ease.
Check out my Fullstack, MERN, and Vanilla JS projects below and past work experiences with Python. When I'm not coding, you'll find me looking for sunshine and either playing soccer, running, hiking, or eating noodles.
Full stack website built with Ruby on Rails, PostgreSQL, and React-Redux.
In the United States, food waste is estimated to be between 30-40 percent of the food supply. This recipe website aims to help use up ingredients that are left in the fridge before they go bad. The search bar takes in individual ingredients and filters recipes that include those ingredients. If we don't have an exact match, inspiration will be pulled up that you can riff on. Say good bye to your leftover bunch of cilantro!
Website built with MERN stack (MongoDB, Express, React, Node)
It can be near impossible for people who don't have plenty of reviews on Yelp or followings on social media to break into their respective markets. Amateur Hour enables beginners to be compensated in ways that augment their credibility.
JavaScript website using Canvas for interactive graphics
Pick a song to dance to. Tap along to the music and follow the choreography dictated by the arrows on the screen. Get a high score by staying on the beat and catching all the arrows!
I have been building tools and dashboards in Python and JavaScript in my roles as a Developer, Data Analyst, and Consultant at Arup.
Led development of a Python web application that was expanded to be offered across all global offices and awarded a company-wide Digital Transformation Award for impact across disciplines.
Read article hereOwned and delivered a Python-based dashboard that automated data processing and visualizations for evaluating equity in all census tracts in the US, saving several days of manual work per project.
Read article hereConceptualized and executed several automations for onboarding that reduced time by 90% through use of HTTP requests. Final product will be launched on all major projects, saving hundreds of hours in manual labor.
Leveraged and adapted an open source Machine Learning model for pedestrian counting and designed workflow in Python to ensure quality of outputs, ensuring effectiveness of automation and reducing time required by 80%.
Executed Monte Carlo simulation to evaluate traffic volume and promote data-driven insights, ensuring the client prepared appropriately for the high-likelihood of a spike in traffic.
Anything pique your interest? I'd love to set up a quick chat. Connect with me on LinkedIn or check out my Github for recent work.